美国私人住宅建设支出与其指标关系的时间序列观察

Xingrui Zhang, Eunhwa Yang, Yunpeng Wang
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引用次数: 0

摘要

目的私人住宅建设支出(PRRESCON)是评估住房供需和经济实力的重要指标。目前,关于prerescon的预报还没有全面的研究。本研究旨在通过使用时间序列方法对prerescon指标进行全面探索,以解决知识空白问题。在实施向量自回归模型之前,对PRRESCON及其所有潜在指标进行格兰杰因果关系检验。以脉冲响应函数的形式对模型进行了大量的解释。脉冲响应函数表明,在任何给定时间,劳动力供应、材料/建筑成本和颁发的建筑许可的上升对10-11个月后的prerescon具有持续的积极影响,具有95%的置信区间。相反,在95%以上的情况下,失业率和住房价值在任何特定时间的上升都对10-11个月后的prerescon产生负面影响。此外,材料/建筑费用在任何时候的上涨,在超过95%的情况下,对7个月后的预研会议产生不利影响。独创性/价值目前关于建筑支出的预测文献只关注参数与国内生产总值和建筑计费指数的关系。这项研究揭示了许多附加指标,其中许多指标与住房开发项目的实施直接相关。据作者所知,这篇论文也是预测文献中第一篇对住宅建设支出进行脉冲响应分析的论文。
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Time series observation of relationship between United States private residential construction spending and its indicators
Purpose Private residential construction spending (PRRESCON) is an important indicator for assessing housing supply/demand and economic strength. Currently, there are no comprehensive studies on PRRESCON forecasting. This study aims to address the gap in knowledge by conducting a comprehensive exploration of indicators for PRRESCON using time series methods. Design/methodology/approach Granger causality test trials were conducted between PRRESCON and all of its potential indicators before the vector autoregression model was implemented. Extensive effort was exerted toward model interpretation in the form of impulse–response functions. Findings Impulse–response functions indicated that the escalation of labor supply, material/construction costs and issued building permits at any given time consistently had a positive impact on PRRESCON 10–11 months later, with a 95% confidence interval. Conversely, the unemployment rate and housing value escalations at any given time were found to have a negative impact on PRRESCON 10–11 months later in more than 95% of the instances. Furthermore, material/construction cost escalations at any given time were shown to have a negative impact on PRRESCON 7 months later in more than 95% of the instances. Originality/value Current forecasting literature on construction spending focuses exclusively on the parameter’s relationship with gross domestic product and the architectural billing index. This study reveals many additional indicators, many of which are directly related to the implementation of housing development projects. The paper is also the first in the body of forecasting literature, to the best of the authors’ knowledge, to conduct impulse–response analysis on residential construction spending.
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CiteScore
2.80
自引率
29.40%
发文量
68
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